Related papers: On Scalable Integrity Checking for Secure Cloud Di…
Efficient discovery of frequent itemsets in large datasets is a crucial task of data mining. In recent years, several approaches have been proposed for generating high utility patterns, they arise the problems of producing a large number of…
Merkle structures are widely used as commitment schemes: they allow a prover to publish a compact commitment to an ordered list $X$ of items, and then efficiently prove to a verifier that $x_i\in X$ is the $i$-th item in it. We compare…
Distributed machine learning enables parallel training of extensive datasets by delegating computing tasks across multiple workers. Despite the cost reduction benefits of distributed machine learning, the dissemination of final model…
Distributed Ledger Technologies (DLT) and Decentralized File Storages (DFS) are becoming increasingly used to create common, decentralized and trustless infrastructures where participants interact and collaborate in Peer-to-Peer…
In-memory data management systems, such as key-value stores, have become an essential infrastructure in today's big-data processing and cloud computing. They rely on efficient index structures to access data. While unordered indexes, such…
Data integrity is important for non-volatile memory (NVM) systems that maintain data even without power. The data integrity in NVM is possibly compromised by integrity attacks, which can be defended against by integrity verification via…
Trusted hardware's freshness guarantee ensures that an adversary cannot replay an old value in response to a memory read request. They rely on maintaining a version number for each cache block and ensuring their integrity using a Merkle…
The use of blockchains for data certification and traceability is now well established in both the literature and practical applications. However, while blockchain-based certification of individual data is clear and straightforward, the use…
Our modern world relies on a growing number of interconnected and interacting devices, leading to a plethora of logs establishing audit trails for all kinds of events. Simultaneously, logs become increasingly important for forensic…
This paper presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block…
Finding the shortest-path distance between two arbitrary vertices is an important problem in road networks. Due to real-time traffic conditions, road networks undergo dynamic changes all the time. Current state-of-the-art methods…
Private Set Intersection (PSI) enables secure computation of set intersections while preserving participant privacy, standard PSI existing protocols remain vulnerable to data integrity attacks allowing malicious participants to extract…
Data-intensive applications fueled the evolution of log structured merge (LSM) based key-value engines that employ the out-of-place paradigm to support high ingestion rates with low read/write interference. These benefits, however, come at…
Database management systems (DBMSs) carefully optimize complex multi-join queries to avoid expensive disk I/O. As servers today feature tens or hundreds of gigabytes of RAM, a significant fraction of many analytic databases becomes…
In this paper, a new and novel data structure is proposed to dynamically insert and delete segments. Unlike the standard segment trees[3], the proposed data structure permits insertion of a segment with interval range beyond the interval…
Distributed Hash Tables (DHTs) have been used in several applications, but most DHTs have opted to solve lookups with multiple hops, to minimize bandwidth costs while sacrificing lookup latency. This paper presents D1HT, an original DHT…
A popular method in practice offloads computation and storage in blockchains by relying on committing only hashes of off-chain data into the blockchain. This mechanism is acknowledged to be vulnerable to a stalling attack: the blocks…
Memory disaggregation can potentially allow memory-optimized range indexes such as B+-trees to scale beyond one machine while attaining high hardware utilization and low cost. Designing scalable indexes on disaggregated memory, however, is…
In this paper, we revisit the question of how the dynamic optimality of search trees should be defined in external memory. A defining characteristic of external-memory data structures is that there is a stark asymmetry between queries and…
Log-Structured Merge (LSM) Trees provide a tiered data storage and retrieval paradigm that is attractive for write-optimized data systems. Maintaining an efficient buffer in memory and deferring updates past their initial write-time, the…